Ocean temperature and salinity responses to
50 year changes in surface conditions
Véronique Lago
B.Sc., Université de Sherbrooke
M.Sc., University of Alberta
Submitted in fulfilment of the requirements for the degree of
Doctor of Philosophy in Quantitative Marine Science
University of Tasmania
Page i This thesis contains no material which has been accepted for the award of any other degree or diploma in any tertiary institution, and to the best of my knowledge and belief, contains no material previously published or written by another person, except where due reference is made in the text of the thesis.
Véronique Lago, B.Sc., M.Sc.
10th February 2017
Published work
Page ii
Statement of co-authorship
The following people and institutions contributed to the publication of work undertaken as part of this thesis:
Véronique Lago, University of Tasmania, Institute for Marine and Antarctic Studies; Centre for Australian Weather and Climate Research, CSIRO, Oceans and Atmosphere and Centre of Excellence for Climate System Science.
Susan E. Wijffels, Centre for Australian Weather and Climate Research, CSIRO, Oceans and Atmosphere.
Paul J. Durack, Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory.
John A. Church, Centre for Australian Weather and Climate Research, CSIRO, Oceans and Atmosphere.
Simon J. Marsland, Centre for Australian Weather and Climate Research, CSIRO Oceans and Atmosphere Flagship.
Page iii
Publications produced as part of this thesis include:
Chapter 2 (Paper 1):
Lago, V., S.E. Wijffels, P.J. Durack, J.A. Church, N.L. Bindoff and S.J. Marsland (2016): Simulating the role of surface forcing on observed multidecadal upper ocean salinity changes. Journal of Climate, 29, pp. 5575-5588. doi: 10.1175/JCLI-D-15-0519.1
Details of the Authors roles to the publication of the work undertaken in Chapter 2:
Véronique Lago (60%), Susan E. Wijffels (10%), Paul J. Durack (10%), John A. Church (5%), Nathaniel L. Bindoff (5%) and Simon J. Marsland (5%)
Véronique Lago contributed to the conception and design of the project, analysis and interpretation of the research and writing.
Susan E. Wijffels contributed to the conception and design of the project, analysis and interpretation of the research and revising the writing.
Paul J. Durack contributed to the analysis and interpretation of the research and revising the writing.
John A. Church contributed to the analysis and interpretation of the research and revising the writing.
Nathaniel L. Bindoff contributed to the analysis and interpretation of the research.
Page iv
To be submitted:
Chapter 3 (Paper 2):
Lago, V., S.E. Wijffels, P.J. Durack, J.A. Church, N.L. Bindoff and S.J. Marsland (in preparation): Subsurface temperature response to surface changes in a 50 year idealized ocean model simulation
Details of the Authors roles to the publication of the work undertaken in Chapter 3:
Véronique Lago (65%), Susan E. Wijffels (9%), Paul J. Durack (9%), John A. Church (7%), Simon J. Marsland (7%) and Nathaniel L. Bindoff (3%)
Véronique Lago contributed to the conception and design of the project, analysis and interpretation of the research and writing.
Susan E. Wijffels contributed to the conception and design of the project, analysis and interpretation of the research and revising the writing.
Paul J. Durack contributed to draft part of the work, the analysis and interpretation of the research and revising the writing.
John A. Church contributed to the analysis and interpretation of the research and revising the writing.
Nathaniel L. Bindoff contributed to the analysis and interpretation of the research.
Page v
Non-published work:
Chapters 1, 4 and 5:
Theses chapters were not written to be submitted for publication. The following authors provided assistance in the research presented in these chapters:
Details of the Authors roles to the publication of the work undertaken in Chapter 1, 4 and 5: Véronique Lago (75%), John A. Church (8%), Susan E. Wijffels (5%), Paul J. Durack (5%), Simon J. Marsland (5%) and Nathaniel L. Bindoff (2%)
Véronique Lago contributed to the conception and design of the project, analysis and interpretation of the research and writing.
John A. Church contributed to the analysis and interpretation of the research and revising the writing.
Susan E. Wijffels contributed to the design of the project, analysis and interpretation of the research and revising the writing.
Paul J. Durack contributed to the analysis and interpretation of the research and revising the writing.
Simon J. Marsland contributed to the design of the project, interpretation of the research and revising the writing.
Page vi
We the undersigned agree with the above stated “proportion of work undertaken” for each of the above published (or submitted) peer-reviewed manuscripts contributing to this thesis:
Signed: __________________________ __________________________
Professor Nathan L. Bindoff Professor Craig Johnson
Supervisor Head of School
Institute for Marine and Antarctic Studies Institute for Marine and Antarctic Studies
University of Tasmania University of Tasmania
Page vii
Abstract
Changes in the global ocean’s temperature and salinity in the last decades are evidence of the Earth’s warming climate. These interior ocean changes are driven by changes in ocean surface fluxes of heat, freshwater and momentum. The warming atmosphere induces increased Sea Surface Temperature (SST) and amplifies the water cycle (evaporation-minus-precipitation) and in turn the Sea Surface Salinity (SSS) pattern. There is strong evidence of significant changes in the temperature and salinity fields in the ocean interior, but little is known of the relative contribution to these trends from each of the surface forcings. Changing surface winds also
impact on ocean circulation and penetration of surface properties into the ocean interior. However, coincident wind changes that have occurred alongside ocean temperature and salinity changes are not well known and available reanalyses that provide our only coherent insight to wind changes are sometimes contradictory. Using a global ocean model, changes from each independent surface forcing is decomposed in idealized experiments. The results show that to reproduce the observed pattern of salinity changes in each major ocean basin using a density space coordinate for the analysis, both the SSS pattern amplification and SST increase need to be taken into consideration. Changes in SSS are transmitted to the subsurface salinity field mainly through subduction while the warming ocean results in migration of isopycnals relative to the mean salinity field creating apparent salinity changes in density space. The SSS pattern amplification results in a subsurface warming in the ventilated gyres and subpolar regions of similar amplitude to that from heat subducted as a result of the increased SST. Warming in the subpolar regions is mainly driven by the reduced convective heat loss as a result of the fresher and less dense surface water which strengthens vertical stratification. To investigate wind changes three different reanalyses datasets are used to compare how imposing the surface forcing due to wind changes affect the subsurface properties. Equatorial cooling between 100 and 300 m across the Pacific and Indian Oceans is consistent across datasets, which is in agreement with a reported strengthening of the trade winds. There is a ~0.5 to ~1oC and ~0.1
Page viii
Page ix
Acknowledgments
I would like to thank the people who gave me assistance and support during my Ph.D. My supervisors Dr. Susan Wijffels, Dr. John Church, Dr. Simon Marsland and Prof. Nathan Bindoff have been very supportive and gave me valuable insights, guided me and taught me how to become a better scientist. You are my inspiration for what I hope to become as a physical oceanographer. I would also like to thank Dr. Paul Durack for his highly appreciated help throughout my Ph.D. and for providing some useful observational data.
Of course, I could not have achieved this Ph.D. without the financial help and support from the Quantitative Marine Science program at the Institute for Marine and Antarctic Studies. The QMS program provides some great opportunity for students. The multi-cultural environment at IMAS makes Hobart all the more an amazing place to live. Furthermore, the Centre of Excellence provided some great opportunities with their great annual winter school, writing workshop and their financial support.
Page x
Table of Contents
Declaration ... i
Statement of co-authorship ... ii
Publications produced as part of this thesis include: ...iii
To be submitted: ... iv
Non-published work:... v
Abstract ... vii
Acknowledgments ... ix
List of Figures ... xiii
List of Tables ... xxi
Chapter 1
: ... 1
Introduction ... 1
1.1 Overview ... 2
1.2 Salinity... 2
1.2.1 Evaporation - Precipitation... 4
1.3 Temperature ... 6
1.4 Winds ... 8
1.5 Model ... 10
1.5.1 Grid ... 12
1.5.2 Forcings ... 15
1.5.3 Restoring ... 15
1.6 Experiments ... 15
References ... 18
Chapter 2
: ... 29
Page xi
Abstract ... 31
2.1 Introduction ... 32
2.2 Methods ... 34
2.3 Results ... 38
2.3.1 Changes on depth surfaces ... 39
2.3.2 Water mass changes ... 40
2.4 Discussion ... 49
Acknowledgments ... 51
References ... 52
Tables ... 57
Figures ... 59
Chapter 3
: ... 67
Subsurface temperature response to surface changes in a 50 year idealized
ocean model simulation ... 67
3.1 Introduction ... 70
3.2 Methods ... 71
3.3 Results ... 73
3.3.1 Changes in temperature in the ocean interior ... 74
3.3.2 Linearity of the temperature experiments ... 79
3.3.3 Regional changes in temperature ... 80
3.3.4 Changes in heat content... 81
3.4 Discussion ... 82
Acknowledgments ... 85
References ... 86
Figures ... 93
Chapter 4
: ... 105
Oceans temperature and salinity response to 50 years changes in wind pattern
... 105
Page xii
4.1 Introduction ... 107
4.2 Methods ... 107
4.3 Results ... 112
4.3.1 Changes in temperature in the ocean interior ... 113
4.3.2 Changes in salinity in the ocean interior ... 122
4.3.3 Correlations ... 123
4.3.4 Linearity ... 125
4.4 Discussion ... 126
Acknowledgments ... 130
References ... 131
Tables ... 136
Figures ... 140
Chapter 5
: ... 151
Conclusion ... 151
5.1 Linearity ... 152
5.2 Salinity... 153
5.3 Temperature ... 154
5.4 Winds ... 155
5.5 Conclusion ... 157
Page xiii
List of Figures
Figure 1.1. a) Surface salinity trend (PSS-78 per 50 years; Durack and Wijffels, 2010) and b) Mean annual evaporation minus precipitation rate (m per year; Josey et al., 1998). In both panels, the black contours are the mean salinity field every 0.5 PSS-78. ____________________________ 4
Figure 1.2. Surface temperature change (oC per 50 years) for multiple observational datasets (a
to e). The black contours are the mean surface temperature every 4oC. Panel f has the zonally
averaged global temperature change for each dataset (oC per 50 years). _________________ 6
Figure 1.3. Outcrops in 1950 (black lines) and 2000 (white lines). The coloured pattern is the mean salinity between 1950 and 2008. (Durack and Wijffels, 2010). _____________________ 7
Figure 1.4. Mean zonal (a) and meridional (b) wind speed at 10 m (m/s) between 1950 and 2008 as the average of three data reanalysis: ERA-40 (Uppala et al., 2005), Japanese 55-year Reanalysis (JRA-55; Kobayashi et al., 2015) and National Oceanic and Atmospheric Administration 20th
Century Reanalysis (NOAA-20CR; Compo et al., 2011). Positive wind speeds are eastward and northward. The black contours are every 2 m/s. _____________________________________ 9
Figure 1.5. Two-dimensional sectional view of the Arakawa B-Grid used in MOM4 and CICE (ACCESS-OM). The indices i and j represent the grid cell number within the grid zonally and meridionally respectively. The tracers, T, are the salinity, temperature and hydrostatic pressure. . The u and v components are respectively the eastward and northward velocities. ________ 12
Page xiv
Figure 1.7. ACCESS-OM tripolar grid every four grid cells in each direction between 80oS and 65oN
(a) and north of 55oN. The colour scale corresponds to the depth of the deepest cell. The lines
show the grid every four grid cells in each direction._________________________________ 14
Figure 2.1. Temperature (a, c) and salinity (b, d) changes for a 50 years period. The top row (a, b) has the changes imposed in the model and the bottom row (c, d); the observed changes for the period 1950-2000. The black contours are the mean field every 3oC and every 0.5 PSS-78 for the
temperature and salinity respectively. The plots on the right show the global zonally averaged temperature (e) and salinity (f) changes from the experiments (solid line) and observations (dashed line). _______________________________________________________________ 59
Figure 2.2. Definition of the spatial domain of the Atlantic (blue), Pacific (red) and Indian (green) oceans for zonal averaging used in this study. ______________________________________ 60
Figure 2.3. Zonally averaged salinity changes (PSS-78 per 50 years) in the control experiment for the Atlantic (left column; a, d), Pacific (central column; b, e) and Indian (right column; c, f) Oceans. The top row is in depth space (a, b, c) and the bottom row in density space (d, e, f). The white contours are the salinity trend every 0.1 PSS-78. The black contours are the mean salinity every 0.5 PSS-78 (thick lines) and 0.25 PSS-78 (thin lines). The scale is the same as used in subsequent plots for comparison. _________________________________________________________ 61
Figure 2.4. Density outcrop at the beginning (black) and at the end (white) for ∆T (a), ∆S (b), ∆T∆S (c) and the observations (d). The colour pattern shows the mean salinity field during the 50 year experiment (PSS-78). _________________________________________________________ 62
Page xv
black contours are the mean salinity every 0.5 PSS-78 (thick lines) and 0.25 PSS-78 (thin lines). ___________________________________________________________________________ 63
Figure 2.6. Zonally averaged salinity changes (PSS-78 per 50 years) on neutral density for the sum of ∆T and ∆S (a, b, c) and zonally averaged salinity trend on neutral density for the sum of ∆T and ∆S minus ∆T∆S (d, e, f). The white contours are the salinity trend every 0.1PSS-78. The black contours are the mean salinity every 0.5 PSS-78 (thick lines) and 0.25 PSS-78 (thin lines). The dotted lines are the levels at which density surfaces are plotted on Figure 8 (24 kg/m3, 25 kg/m3
and 26.75 kg/m3). ____________________________________________________________ 64
Figure 2.7. Zonally averaged salinity changes (PSS-78 per 50 years) on neutral density in the Atlantic (a, b, c, d), Pacific (e, f, g, h) and Indian (i, j, k, l) Oceans. The columns correspond from left to right to the observations, ∆T∆S, ∆T and ∆S. The white contours are the salinity trend every 0.1 78. The black contours are the mean salinity every 0.5 78 (thick lines) and 0.25 PSS-78 (thin lines). The dotted lines mark the σ=24 kg/m3, σ= 25 kg/m3 and σ=26.75 kg/m3 which we
examine in more detail. _______________________________________________________ 65
Figure 2.8. Salinity changes (PSS-78 per 50 years) on neutral density surfaces at 24 kg/m3 (a, b, c,
d), 25 kg/m3 (e, f, g, h) and 26.75 kg/m3 (i, j, k, l). The columns correspond from left to right to
the observations, the temperature increase experiment, the salinity pattern increase experiment and both increased respectively. The black contours are the mean salinity every 0.5 PSS-78 (thick lines) and 0.25 PSS-78 (thin lines). _______________________________________________ 66
Figure 3.1. Temperature (oC ; a, c) and salinity (PSS-78; b, d) changes for a 50 years period. The
top row (a, b) has the changes imposed in the model and the bottom row (c, d); the observed changes for the period 1950-2000. The black contours are the mean field every 3oC and every 0.5
Page xvi
Figure 3.2. Zonally averaged potential temperature changes (oC per 50 years) in the control
experiment for the Atlantic (a, d) Pacific (b, e) and Indian (c, f) Oceans. The scale matches the scale use for the results. The black contours are the mean temperature every 4 oC and the white
contours are the changes every 0.1 oC. ___________________________________________ 94
Figure 3.3. Comparison of the zonally averaged potential temperature changes (oC per 50 years)
in the Atlantic (a,b,c,d) Pacific (e,f,g,h) and Indian (i,j,k,l) Oceans for the top 2000m for different observational datasets. The columns correspond from left to right to the datasets of Durack and Wijffels (2010), Ishii and Kimoto (2009), Good et al. (2013), Levitus et al. (2012) and Smith and Murphy (2007). The white contours are the temperature trend every 0.5oC. The black contours
are the mean temperature every 8oC (thick lines) and 4oC (thin lines). __________________ 95
Figure 3.4. Zonally averaged potential temperature changes (oC per 50 years) in the Atlantic
(a,b,c,d) Pacific (e,f,g,h) and Indian (i,j,k,l) Oceans for the top 2000m of the ocean. The columns correspond from left to right to the observations, ΔTΔS, ΔT and ΔS. The white contours are the temperature trend every 0.5oC. The black contours are the mean temperature every 8oC (thick
lines) and 4oC (thin lines). The dashed grey lines are the latitudes selected as the limit for the
ventilated gyres and the high latitudes as described in the results. _____________________ 96
Figure 3.5. Mean temperature change due to each component of the heat budget for each ocean basin between 30oS and 30oN. The paler solid line is the total temperature change from all of the
components and the darker solid line is the temperature change directly from the model’s temperature outputs. _________________________________________________________ 97
Figure 3.6. Total vertical transport change integrated between 30oS and 30oN in the Atlantic (a),
Page xvii
dashed grey line is the mean vertical transport in the control experiment divided by 10 to give an indication of the mean transport’s direction._______________________________________ 98
Figure 3.7. Total average temperature change for the Atlantic (a,b,c,d), the Pacific (e,f,g,h) and the Indian Ocean (I,j,k). The first column has the average temperature change for all latitudes (a,e,i), the second column the latitudes between 47oS and 47oN (b,f,j), the third column for
latitudes lower than 47oS (c,g,k) and the last column for latitudes higher than 47oN (d,h). ___ 99
Figure 3.8. Mixed layer depth in the Weddell Sea (panels a,b,c), Nordic Seas (panels d,e, f) and Irminger Sea (panels g,h,i). For each experiment, the grey dashed line is the MLD at year 1, the white dashed line is the 50 years MLD trend added to the year 1 yearly cycle and the solid black line is the mean annual cycle. The colours in panels a to i are the mean density at this location. The location is chosen where the deepest MLD occurs within the grey box in panels j, k and l, as indicated by the magenta dot. The colours in j, k and l are the MLD changed (in meters per 50 years). ____________________________________________________________________ 100
Figure 3.9. Mean temperature change due to each component of the heat budget in the North Pacific Ocean between 30oN and 65oN. The paler solid line is the total temperature change from
all of the components and the darker solid line is the temperature change directly from the model’s temperature outputs. _________________________________________________ 101
Figure 3.10. Zonally averaged temperature changes (oC per 50 years). The top row (a, b, c) is for
the sum of ΔT and ΔS and the bottom row (d, e, f) for the sum of ΔT and ΔS minus ΔTΔS the scale matches the corresponding scale in Figure 4. The white contours are the temperature trend every 0.5oC (a,b,c) and every 0.1 oC (d,e,f). The black contours are the mean temperature every 8oC
Page xviii
Figure 3.11. Temperature changes (oC per 50 years) at 100m (a,b,c,d), 300m (e,f,g,h) and 500m
(i,j,k,l). The columns corresponds from left to right to the observations, ΔTΔS, ΔT and ΔS. The black contours are the mean temperature every 8oC (thick lines) and 4oC (thin lines). _____ 103
Figure 3.12. Depth integrated heat content (W/m2) for each experiment and observations
integrated from 0m to 2000m zonally averaged (a) and mapped (b,c,d,e). The black contours are the mean heat content every 0.5x1010 W/m2. _____________________________________ 104
Figure 4.1. Zonal wind change (a,c,e,g,i) and meridional wind change at 10 m (b,d,f,h,j) imposed at the surface (m/s per 50 years) for each dataset used in the experiments. Panels k and l shows the mean COREv2 wind (zonal velocity: panel k and meridional velocity: panel l). The years range used to produce the 50 years linear trends are ERA-40: 1958-2003; JRA-55: 1958-2014; NOAA-20CR: 1950-2008 and CMIP5: 1950-2008. The black contours are the mean field every 2 m/s. Panel m shows the zonally averaged wind speed change (m/s per 50 years) for each dataset used in the experiments. __________________________________________________________ 140
Figure 4.2. Zonal wind stress change (a,c,e,g,i) and meridional wind stress change (b,d,f,h,j) at the surface (N/m2 per 50 years) for each wind experiment. Panels k and l shows the annual mean
COREv2 wind stress (zonal wind stress: panel k and meridional wind stress: panel l). The black contours are the mean field every 0.05 N/m2. Panel m shows the zonally averaged wind stress
change (N/m2 per 50 years) for each wind experiment. _____________________________ 141
Figure 4.3. Wind stress curl change (a,b,c,d,e) at the surface (107 N/m2 per 50 years) for each
wind experiment (upper colourbar). Panel f shows the annual mean COREv2 wind stress curl (lower colourbar). The black contours are the mean field at 0 N/m2. Panel g shows the zonally
averaged wind stress curl change (107 N/m2 per 50 years) for each wind experiment. _____ 142
Figure 4.4. Comparison of the zonally averaged potential temperature changes (oC per 50 years)
Page xix
experiment. The columns correspond from left to right to the observations, ∆ERA-40, ∆JRA-55, ∆NOAA-20CR and ∆CMIP5. The white contours are the temperature trend every 0.5oC. The black
contours are the mean temperature every 8oC (thick lines) and 4oC (thin lines). __________ 143
Figure 4.5. Comparison of the zonally averaged potential temperature changes (oC per 50 years)
in the Atlantic (a,b,c,d,e) Pacific (f,g,h,I,j) and Indian (k,l,m,n,o) Oceans. The columns correspond from left to right to the observation, the ∆T∆S∆Mean experiment, the sum of ∆CMIP5 and ∆T∆S, the ∆MeanTrend experiment and the ∆T∆S experiment. The white contours are the temperature trend every 0.5oC. The black contours are the mean temperature every 8oC (thick lines) and 4oC
(thin lines). ________________________________________________________________ 144
Figure 4.6. Comparison of the meridionally averaged potential temperature changes (oC per 50
years) between 5oS and 5oN along longitude for the observations (a) and the wind experiments
(c, e, g, I, k, m and o) The white contours are the temperature trend every 0.5oC. The black
contours are the mean temperature every 6oC (thick lines) and 2oC (thin lines). Above the
temperature change of each experiment are the corresponding mean zonal wind stress changes (N/m2 per 50 years) (b, d, f, h, j, l and n). _________________________________________ 145
Figure 4.7. Temperature changes (oC per 50 years) at 100m (a,b,c,d,e), 300m (f,g,h,i,j) and 500m
(k,l,m,n,o). The columns correspond from left to right to the observations, ΔERA-40, ΔJRA-55, ΔNOAA-20CR and ΔCMIP5. The black contours are the mean temperature every 8oC (thick lines)
and 4oC (thin lines). __________________________________________________________ 146
Figure 4.8. Temperature changes (oC per 50 years) at 100m (a,b,c,d,e), 300m (f,g,h,i,j) and 500m
Page xx
Figure 4.9. Comparison of the zonally averaged salinity changes (PSS-78 per 50 years) in the Atlantic (a,b,c,d,e) Pacific (f,g,h,i,j) and Indian (k,l,m,n,o) Oceans. The columns correspond from left to right to the observations, ∆ERA-40, ∆JRA-55, ∆NOAA-20CR and ∆CMIP5. The white contours are the salinity trend every 0.1 PSS-78. The black contours are the mean salinity every 0.5 PSS-78 (thick lines) and 0.25 PSS-78 (thin lines). ________________________________ 148
Figure 4.10. Comparison of the zonally averaged salinity changes (PSS-78 per 50 years) in the Atlantic (a,b,c,d,e) Pacific (f,g,h,i,j) and Indian (k,l,m,n,o) Oceans. The columns correspond from left to right to the observations, the ∆T∆S∆Mean experiment, the sum of ∆T∆S and ∆CMIP5, the ∆MeanTrend experiment and the ∆T∆S experiment. The white contours are the salinity trend every 0.1 PSS-78. The black contours are the mean salinity every 0.5 PSS-78 (thick lines) and 0.25 PSS-78 (thin lines). __________________________________________________________ 149
Figure 4.11. Zonally averaged temperature and salinity changes (oC and PSS-78 per 50 years) in
the Atlantic (a,b,c,d) Pacific (e,f,g,h) and Indian (i,j,k,l) Oceans. The first and third columns are the sum of changes in ∆T∆S and ∆MeanTrend and the second and fourth columns are the changes in ∆T∆S∆Mean minus the sum of changes in ∆T∆S and ∆MeanTrend. The white contours are the temperature trend every 0.5 oC and salinity trend every 0.1 PSS-78 for the temperature and
salinity plots respectively. The black contours in the temperature plots (first and second columns) are the mean temperature every 8 oC (thick lines) and every 4 oC (thin lines). The black contours
Page xxi
List of Tables
Table 1.1. Summary of the surface boundary condition imposed in each idealized experiment. ___________________________________________________________________________ 16
Table 2.1. List of experiment nomenclature and corresponding imposed ocean surface conditions. __________________________________________________________________ 57
Table 2.2. Spatial correlation coefficients for zonally averaged salinity change patterns in density space (see Figure 2.7). The first column has the correlation between each experiment and observations and the second and third column the correlation between each experiment. The control experiment has been subtracted prior to calculation in all cases. ________________ 58
Table 4.1. List of models used for the CMIP5 multi-model ensembles wind pattern experiment. __________________________________________________________________________ 136
Table 4.2. List of experiment nomenclature and corresponding imposed ocean surface conditions. _________________________________________________________________ 137
Table 4.3. Correlation coefficients for the zonal temperature changes per ocean basin. ____ 138
Page 1
Chapter 1
:
Page 2
1.1
Overview
The oceans have the capacity to influence regional and global climate through variations in global and regional energy storage. The ocean has a heat capacity about a thousand times that of the atmosphere, allowing it to store and redistribute energy (Levitus et al., 2005). Heat storage in the deeper ocean would not be possible without ocean dynamics. Advective and convective processes, which are a response to momentum and density gradients imposed at the surface, allow ocean surface properties to be carried into the ocean interior. The variations in density result from changes in the temperature and salinity fields, which at the surface result from air-sea interactions.
In recent decades, changes have been observed simultaneously in the ocean and in the atmosphere. In the ocean, changes include increases in temperature and changes to salinity both at the surface and ocean interior (e.g. Levitus et al., 2000; Dickson et al., 2002, Curry et al., 2003; Boyer et al., 2005; Levitus et al., 2005; Hosoda et al., 2009; Durack and Wijffels, 2010; Helm et al., 2010; Skliris et al., 2014). These changes are reflected in the atmospheric boundary
interaction which has led to an increased ocean heat uptake (Levitus et al., 2000; Ishii et al., 2005; Purkey and Johnson, 2010; Kuhlbrodt and Gregory, 2012; Levitus et al., 2012), an amplification of the hydrological cycle (Bindoff et al., 2007; Durack and Wijffels, 2010; Helm et al., 2010; Durack et al., 2012) and changes to wind patterns (Huang et al., 2006; Seidel et al., 2008).
1.2
Salinity
Page 3
requires more energy to mix the surface layer with the denser subsurface water. Alternatively, an increased surface salinity leads to greater vertical mixing by increasing the surface density.
Some regions are particularly sensitive to changes in salinity due to local mixing processes and a surface anomaly can be transferred to large areas of the subsurface ocean. For example, the subpolar North Atlantic has sites of deep water formation through seasonally driven deep convection. The convection is produced when the surface increases in density due to both cooling and brine rejection associated with sea-ice formation (Lazier et al., 2002; Yashayaev et al., 2007; Dickson et al., 2002). The Southern Ocean also has deep convection, mainly in the Weddell and Ross Seas, which is affected by changes in surface salinity (e.g. Marsland and Wolff, 2001; Stammer, 2008; de Lavergne et al., 2014; Kjellsson et al., 2015; Morrison et al., 2015). Water masses formed in both of these regions spread through large parts of the global oceans. The subpolar North Pacific does not have the equivalent processes due to stronger precipitation which maintains a stronger stratification that prevents large scale open-ocean convections (Warren, 1983; Emile-Geay et al., 2003).
Page 4
1.2.1
Evaporation - Precipitation
Figure 1.1. a) Surface salinity trend (PSS-78 per 50 years; Durack and Wijffels, 2010) and b) Mean annual evaporation minus precipitation rate (m per year; Josey et al., 1998). In both panels, the black contours are the mean salinity field every 0.5 PSS-78.
[image:27.612.76.542.81.488.2]Page 5
12.2 ± 1.2 Sv in precipitation. Terrestrial runoff added to meltwater from snow and glacier accounts for approximately only 1.25 ± 0.1 Sv. Changes in the E-P pattern could destabilize the upper-ocean stratification and lead to changes in salinity in the ocean interior (Skliris et al., 2014).
The water cycle depends on the exchanges between the atmosphere and the ocean through evaporation-precipitation. Approximately 78% of the total rain falls over the ocean and about 86% of the atmospheric water vapour has been evaporated from the ocean (Baumgartner and Reichel, 1975, Adler et al., 2003). Even though estimates of E-P are assessed from the local wind speed, temperature and humidity dependence as well as satellite images (Zhang et al., 2007), the incomplete E-P data over the ocean poses a challenge in quantifying these fields, especially in a time varying point of view. The global evaporation pattern is strongest over the subtropical gyres and the western boundary currents and weaker at higher latitudes and around the equator (Schanze et al., 2010). The pattern of time averaged precipitation rate has higher precipitation in the western boundary currents, the higher latitudes and around the equator, but weaker precipitation in the subtropical gyres.
The atmosphere’s capacity to hold water vapour is approximately exponentially dependent on temperature according to the Clausius-Clapeyron relation, that is, for a 1oC increase in
temperature, the air can hold a corresponding 7% increased water vapour (Schmitt, 2009). Thus, assuming unchanged physics, the evaporative component of the water cycle is expected to increase. The SST has increased by ~0.5oC over the past 50 years, which suggests an
approximately 4% increase in the global water cycle (Trenberth et al., 2007, Durack et al., 2012). However, the corresponding change to SSS has amplified by about 8% (Curry et al., 2003; Boyer et al., 2005; Hosoda et al., 2009; Helm et al., 2010; Skliris et al., 2014; Durack et al., 2012). This
Page 6
1.3
Temperature
The mean global ocean surface temperature has increased by around 0.5oC per 50 years over the
past decades (Figure 1.2; Ishii et al., 2005; Rayner et al., 2006; Smith and Murphy, 2007; Solomon et al., 2007, Ishii and Kimoto, 2009; Durack and Wijffels, 2010; Levitus et al., 2012; Good et al.,
[image:29.612.77.540.304.574.2]2013). The SST increase is more pronounced in the North Atlantic and lesser in the Southern Ocean (Figure 1.2a; Marshall et al., 2014). However, the observed warming in the Southern Ocean is likely underestimated due to the sparse observations (Gille, 2002; Gouretski and Koltermann, 2007; Durack et al., 2014), the mean surface temperature change is significantly smaller south of 55oS (Figure 1.2b).
Figure 1.2. Surface temperature change (oC per 50 years) for multiple observational datasets (a to e). The black contours are the mean surface temperature every 4oC. Panel f has the zonally averaged global temperature change for each dataset (oC per 50 years).
Page 7
[image:30.612.75.547.148.427.2]the broad-scale long-term warming of the global ocean has therefore led to a general poleward migration of isopycnals. The lateral shifts in certain regions are estimated to be at the scale of 50 to 100 km over a 50 years period (Durack and Wijffels, 2010) (Figure 1.3).
Figure 1.3. Outcrops in 1950 (black lines) and 2000 (white lines). The coloured pattern is the mean salinity between 1950 and 2008. (Durack and Wijffels, 2010).
The increased surface temperature is transmitted to the ocean interior through subduction, convection, advection and mixing and increases the ocean heat content (Meehl et al., 2011; Balmaseda et al., 2013). It also impacts both the circulation by affecting local density gradients and sea level by increasing the steric height (Church et al., 2004; Domingues et al., 2008, Levitus et al., 2012). Levitus et al. (2000) showed that the volume mean warming of the world’s ocean
heat content from the mid 1950s to mid 1990s represents approximately a 0.06oC temperature
increase. The upper 75 m of ocean warmed at a rate of 0.11oC per decade between 1971 and
Page 8
This warming of the upper layers of the oceans is global and roughly similar in each basin at equivalent latitudes. Exceptions include cooling in the South Pacific, due to local decadal variations (Barnett et al., 2005). In the North Atlantic Deep Water cooling is observed after the renewal of deep convection post 1970s (Dickson et al., 2002). Finally, the South Indian Ocean has some subsurface cooling due to variations in the Indonesian Throughflow (ITF) and wind patterns (Alory et al., 2007; Schwarzkopf and Böning, 2011).
1.4
Winds
The atmospheric winds are driven by radiative forces. The surface zonal wind speed over the ocean comprises the trade winds in the equatorial and subtropical regions and the westerlies at high latitude (Figure 1.4a). The surface wind transfers its kinetic energy into both kinetic and potential energy to the ocean surface (Wunsch and Ferrari, 2004). The force applied on the surface of the ocean depends quadratically on the atmospheric surface wind speed (Zhai et al., 2013):
𝜏 = 𝜌𝑎𝑐𝑑|𝑈10− 𝑢0|(𝑈10− 𝑢0)
Where τ is the surface wind stress, ρa is the sea level air density, cd is a drag coefficient, u0 is the surface velocity of the ocean and U10 is the wind velocity at 10 m. The surface wind stress affects the ocean mixing and circulation in the Ekman layer (Wunsch and Ferrari, 2004).
Page 9
the ocean dynamics of this region, which explains the importance of the wind stress in the Southern Ocean (Figure 1.4).
[image:32.612.71.543.291.574.2]At the equator the Hadley atmospheric circulation converge at the surface, where the southward meridional surface wind velocity in the Northern Hemisphere meets the northward meridional surface wind velocity in the Southern Hemisphere (Figure 1.4b). At low latitudes, the trade winds drive the westward equatorial circulation. The trade winds drive meridional Ekman transport at the surface of the ocean. The Ekman transport changes sign at the equator due to the change of hemisphere which change the sign of the Coriolis parameter. This change of sign induces a divergence at the equator which drives equatorial upwelling in the ocean.
Page 10
The wind pattern has changed in the past decades, however, due to sparse and limited observations there are uncertainties in the exact nature of these changes (Wu et al., 2005; Krueger et al., 2013). Data reanalyses point to a strengthening of the westerlies at high latitudes and a possible poleward shift (Swart and Fyfe, 2012). There is also evidence of an increased to the trade winds over the tropical Pacific (Merrifield, 2011). Additionally, there are signs of a poleward extension of the Hadley circulation (Wu et al., 2012).
The effect of wind stress on the ocean circulation and dynamics is well studied and understood. However, because of the sparse wind observations, the nature of the changes in the wind field and its effect on the ocean circulation and mixing is still not fully understood. The strengthened westerlies over the Southern Ocean might drive an increase in eddy diffusivity leading to an increased poleward heat flux (Meredith and Hogg, 2006; Fyfe et al., 2007; Hogg et al., 2008). Additionally, Merrifield (2011) suggests that increased trade winds in the equatorial Pacific drive a sea level height increase on the western side of the Pacific.
1.5
Model
Page 11
The version of ACCESS-OM used here follows the same physical parameterisations as Bi et al.
(2013; Table 1) with two exceptions: the explicit convection and the near-equator reduction of
vertical diffusion. The advection of tracers uses the multi-dimensional flux limited scheme for
conservative temperature, salinity, and age tracers (Sweby 1984, Hundsdorfer and Trompert
1994). The horizontal friction uses Smagorinsky isotropic biharmonic friction as formulated by
Griffies and Hallberg (2000). Convection is implicit using vertical diffusivity following Killworth et
al. (1991). The background vertical mixing in the deep ocean is 1 m2/s2. In the upper ocean, the
vertical mixing follows the Large et al. (1994) k-parametrisation profile (KPP) mixed layer scheme.
The neutral physics are parameterised following the scheme described by Gent and McWilliams
(1990) in which the diffusion is relaxed by bringing neutral directions toward surfaces of constant
generalized vertical coordinate rather than constant geopotential surfaces with baroclinic closure
of the thickness diffusivity (Ferrari et al. 2010). The isoneutral diffusivity has a background value
of 600 m2/s2 following Redi (1982). The parameterisation for tidal mixing in the abyssal ocean
follows Simmons et al. (2004) and the parameterization of barotropic coastal tidal dissipation
according to Lee et al. (2006). The shelf waters overflow at high latitudes are parameterised using
the sigma transport scheme of Beckmann and Doescher (1997) with the downslope mixing
scheme from Griffies (2009).
The model was spun-up for 500 years with normal year COREv2 forcing which provided a relatively state for the commencement of the experiments. Like most similar models, ocean adjustment continues after the completion of the spin-up in the deep water masses (Griffies et al., 2009; Bi et al., 2013). To account for this ongoing drift, a control experiment is subtracted
from each other experiment in all data presented.
Page 12
The Atlantic Meridional Overturning Circulation and the Pacific equatorial circulation are closed to observations. The Antarctic Circumpolar Current is too strong, but is within the range of simulated with other CORE models (Bi et al., 2013).
1.5.1
Grid
The ocean and ice models, MOM4 and CICE, are both structured with Arakawa B-grids (Arakawa and Lamb, 1977; Figure 1.5 and Figure 1.6). This spatial discretization defines the location of the horizontal velocity components at the northeast corner of each cell, half distance between the
centre of two adjacent cells. The vertical velocity is at the centre of the bottom face of each cell. The tracers, salinity, temperature, density and hydrostatic pressure, are diagnosed at the centre of a cell.
[image:35.612.157.459.327.610.2]Page 13
In the ocean model, MOM4, the equations of state are discretised on a fixed curvilinear grid. The discretization nature of the grid generates differences with the physics of reality. Griffies et al. (2000) summarized the strengths and weaknesses of an Arakawa B-grid for an ocean model. This grid type simulates well the gravity waves and geostrophic currents at coarser resolution. B-grids are also superior for boundary currents, fronts and Rossby waves. However, in consideration to smaller-scale processes and finer resolution models, B-grids are not an ideal choice. Generally, B-grids are preferred for coarse resolution models for their superiority in resolving flows at these resolutions. In ACCESS-OM, the Arakawa B-grid model is an appropriate choice for the resolution.
Figure 1.6. Three-dimensional view of an Arakawa B-Grid cell as used in MOM4 and CICE (ACCESS-OM). The indices i, j and k represent the grid cell number within the grid zonally, meridionally and vertically respectively. The tracers, T, are the salinity, temperature and hydrostatic pressure. The u, v and w components are respectively the eastward, northward and upward velocities.
The grid is a tripolar grid to avoid discontinuities at the North Pole (Murray, 1996) (Figure 1.7). This grid follows the geographical coordinates between 78oS and 65oN. The grid is not defined
over the interior continent of Antarctica. In the Arctic Ocean, north of 65oN, two poles are
[image:36.612.154.454.259.482.2]Page 14
discontinuity of a pole within the ocean limits. The grid has a 1o resolution in the zonal direction.
In the meridional direction, the resolution varies from ¼o at 78oS to 1o at 30oS and refines to ⅓o
between 10oS and 10oN.
[image:37.612.71.546.291.627.2]In the vertical direction, there are 50 levels between 0 and 6000 m. The thickness of the levels varies from finer near the surface, where smaller scale processes occur, to thicker at depth. The variations in the topography are approximated through a partial cell method which has been shown to improve a model’s ocean simulation (Adcroft et al., 1997, Myers and Deacu, 2004). The partial cell method keeps the cell rectangular, but allows the deeper cell to vary in thickness according to the local bathymetry.
Page 15
1.5.2
Forcings
The COREv2 normal year dataset from Large and Yeager (2004) is used in MATM. This dataset acts as a substitute for a complete atmospheric model integrated to an ocean only or ocean-ice model. It prescribes the atmospheric boundary conditions over both the ocean and sea ice.
The COREv2 forcing is on a spherical grid of 192 longitudinal points by 94 latitudinal points. Due to timestep differences, the field is applied to the model with temporal interpolation. The COREv2 precipitation field varies monthly, the shortwave and longwave radiation daily; and
temperature, humidity, zonal velocity, meridional velocity and sea level pressure six-hourly.
1.5.3
Restoring
The salinity restoring is applied at the surface of the ocean through virtual salt flux. A virtual salt flux is a modelling strategy used for rigid-lid approximation of the ocean, i.e. fixed volume. The surface salinity is corrected to the restoring condition by this virtual salt flux. The freshwater fluxes at the surface are input by locally changing the surface salinity rather than imposing a volume flux of freshwater. This technique can be summarized as a parameterization of salt flux locally input or output at the surface of the ocean. This technique induces only small errors (Yin et al., 2010) and can be considered as a valid approximation. In our experiments, we also use
temperature restoring at the surface to impose a virtual heat flux. The virtual heat flux damps the SST towards a restoring field.
1.6
Experiments
Page 16
Table 1.1. Summary of the surface boundary condition imposed in each idealized experiment. Experiment name Temperature
uniform increase (oC)
Salinity pattern amplification (%)
Wind change
Control 0 0 -
∆T 0.5 0 -
∆S 0 8 -
∆T∆S 0.5 8 -
∆ERA-40 0 0 ERA-40
∆JRA-55 0 0 JRA-55
∆NOAA-20CR 0 0 NOAA-20CR
∆CMIP5 0 0 CMIP5
∆MeanTrend 0 0 MeanTrend
∆T∆S∆MeanTrend 0.5 8 MeanTrend
The surface temperature increase, salinity pattern amplification and wind change are applied individually and together (Table 1.1). A period of 50 years will be the main focus to enable comparisons with the 50 years trends observations of salinity and temperature from 1950 to 2008 compiled by Durack and Wijffels (2010). The temperature is linearly increased by 0.5oC
between 55oS and 60oN, which compares well with the observed mean surface temperature
increase for the same time period. The observed sea surface temperature has warmed north of 60oN (Figure 1.2). However, because of the experimental setup through surface restoring
increasing linearly throughout the year, increasing the sea surface temperature north of 60oN
would warm the ocean surface under the sea ice, which is unrealistic. In order to avoid this problem, we impose no warming at high latitudes and concentrate the study mainly to the ventilated gyres area. The sharp change in temperature at the edge of our warming domain creates a gradually amplifying sharp gradient at the surface. However, within the limits of the change in temperature we impose (0.5oC after 50 years), this gradient dissipates locally in the
upper ~100 m.
Page 17
the 8% amplification by linearly amplifying the difference with the mean salinity over the intra-annual monthly cycle.
Finally, wind speed changes from three data reanalyses are tested; ERA-40 (Uppala et al., 2005), JRA-55 (Japanese 55-year Reanalysis; Kobayashi et al., 2015) and NOAA-20CR (National Oceanic and Atmospheric Administration 20th Century Reanalysis; Compo et al., 2011) along with the wind
speed trends in the CMIP5 historical multi-model ensemble (Taylor et al., 2012). The wind change experiments impose the 50 years trends per grid cell from each of these datasets. An additional wind trend dataset is created from the average of the trends from all three reanalyses (MeanTrend). The wind trends are imposed in a linear change over the COREv2 normal year intra-annual field to avoid discontinuity from the spin-up. Two additional experiments where surface temperature changes and surface salinity pattern amplification are applied together with fixed wind and with MeanTrend wind change are also performed to identify how these changes act together.
Page 18
References
Adcroft, A., C. Hill, J. Marshall, 1997: Representation of topography by shaved cells in a height coordinate ocean model. Monthly Weather Review, 125, pp. 2293–2315.
Adler, R., G. Huffman, A. Chang, R. Ferraro, P. Xie, J. Janowiak, B. Rudolf, U. Schneider, S. Curtis, D. Bolvin, et al., 2003: The version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present). Journal of Hydrometeorology, 4, pp. 1147–1167.
Alory, G., S. Wijffels, and G. Meyers, 2007: Observed temperature trends in the Indian Ocean over 1960–1999 and associated mechanisms. Geophysical Research Letters, 34, L02606. doi:10.1029/2006GL028044
Arakawa, A., and V.R. Lamb, 1977: Computational design and the basic dynamical processes of the UCLA general circulation model. Methods in Computational Physics, 17, pp. 173–265.
Balmaseda, M.A., K.E. Trenberth and E. Kallen, 2013: Distinctive climate signals in reanalysis of global ocean heat content. Geophysical Research Letters, 40, pp. 1754-1759. doi:10.1002/grl.50382
Barnett, T.P., D. W. Pierce, K. M. AchutaRao, P.J. Gleckler, B. D. Santer, J.M. Gregory, W.M. Washington, 2005: Penetration of Human-Induced Warming into the World’s Oceans. Science, 309, pp. 284-287. doi:10.1126/science.1112418
Baumgartner, A. and E. Reichel. 1975: World water balance: mean annual global, continental and maritime precipitation, evaporation and runoff. Elsevier Scientific, 182 pp.
Page 19
Bi, D., S.J. Marsland, P. Uotila, S. O’Farrell, R. Fiedler, A. Sullivan, S.M. Griffies, X. Zhou, and A.C. Hirst, 2013: ACCESS-OM: the Ocean and Sea ice Core of the ACCESS Coupled Model. Australian Meteorology and Oceanography Journal, 63(1), pp. 213-232.
Bindoff, N.L., and T.J. McDougall, 1994: Diagnosing climate change and ocean ventilation using hydrographic data. Journal of Physical Oceanography, 24, pp. 1137–1152.
Boyer, T.P., S. Levitus, J.I. Antonov, R.A. Locarnini, R. and H.E. Garcia (2005) Linear trends in salinity for the World Ocean, 1955-1998. Geophysical Research Letters, 32, L01604. doi:10.1029/2004GL021791
Boyer, T.P., J.I. Antonov, S. Levitus, and R. Locarnini, 2005: Linear trends of salinity for the world ocean, 1955-1998. Geophysical Research Letters, 32, L01604. doi:1029/2004GL021791
Compo, G. P., Whitaker, J. S., Sardeshmukh, P. D., Matsui, N., Allan, R. J., Yin, X., Gleason, B. E., Vose, R. S., Rutledge, G., Bessemoulin, P., Brönnimann, S., Brunet, M., Crouthamel, R. I., Grant, A. N., Groisman, P. Y., Jones, P. D., Kruk, M. C., Kruger, A. C., Marshall, G. J., Maugeri, M., Mok, H. Y., Nordli, Ø., Ross, T. F., Trigo, R. M., Wang, X. L., Woodruff, S. D. and Worley, S. J., 2011: The Twentieth Century Reanalysis Project. Quaterly Journal of the Royal Meteorological Society, 137, pp. 1–28. doi:10.1002/qj.776
Church, J.A., N.J., White, R. Coleman, K. Lambeck and J.X. Mitrovica, 2004: Estimates of the Regional Distribution of Sea Level Rise over the 1950–2000 Period. Journal of Climate, 17, pp. 2609-2625.
Curry, R., R. Dickson and I. Yashayaev, 2003: A change in the freshwater balance of the Atlantic Ocean over the past four decades. Nature, 426, pp. 826-829.
Page 20
Dickson, R. R., I. Yashayaev, J. Meincke, W. Turrell, S. Dye and J. Holfort, 2002: Rapid Freshening of the deep North Atlantic over the past four decades. Nature, 416, pp. 832-837.
Domingues, C.M., J.A. Church, N.J. White, P.J. Gleckler, S.E. Wijffels, P.M. Barker and J.R. Dunn, 2008: Improved estimates of upper-ocean warming and multi-decadal sea-level rise. Nature, 453, pp. 1090-1093. doi:10.1038/nature07080
Durack, P.J. and S. E. Wijffels, 2010: Fifty-year trends in the global ocean salinities and their relationship to broad-scale warming. Journal of Climate, 23, pp. 4342-4362.
Durack, P.J., S.E. Wijffels, R.J. Matear, 2012: Ocean salinities reveal strong global water cycle intensification during 1950 to 2000. Science, 336, pp. 455-458.
Durack, P.J., P.J. Gleckler, F.W. Landerer and K. E. Taylor, 2014: Quantifying underestimates of long-term upper-ocean warming. Nature Climate Change, 4, pp. 999-1005. doi:10.1038/NCLIMATE2389
Emile-Geay, J., M.A. Cane, N. Naik, R. Seager, A.C. Clement amd A. can Geen, 2003: Warren revisited: Atmospheric freshwater fluxes and “Why is no deep water formed in the North Pacific”. Journal of Geophysical Research: Oceans, 108(C6). doi:10.1029/2001JC001058
Ferrari, R., S.M. Griffies, G. Nurser and G.K. Vallis, 2010: A Boundary Value Problem for the Parameterized Mesoscale Eddy Transport. Ocean Modelling, 32, pp. 143–156.
Fyfe, J.C., O.A. Saenko, K. Zickfeld, M. Eby, and A.J. Weaver, 2007: The Role of Poleward-Intensifying Winds on Southern Ocean Warming. Journal of Climate, 20, pp. 5391–5400. doi:10.1175/2007JCLI1764.1
Gent, P.R. and J.C. McWilliams, 1990: Isopycnal mixing in ocean circulation models. Journal of Physical Oceanography, 20, pp. 150–155.
Page 21
Good, S.A., M.J. Martin and N.A. Rayner, 2013: EN4: Quality controlled ocean temperature and
salinity profiles and monthly objective analyses with uncertainty estimates. Journal of
Geophysical Research: Oceans, 118, pp. 6704-6716. doi:10.1002/2013JC009067
Gould, J., D. Roemmich, S. Wijffels, H. Freeland, M. Ignaszewsky, X. Jianping, S. Pouliquen, Y. Desaubies, U. Send, K. Radhakrishnan, K. Takeuchi, K. Kim, M. Danchenkov, P. Sutton, B. King, B. Owens and S. Riser, 2004: Argo profiling floats bring new era of in situ ocean observations. Eos, Transactions American Geophysical Union, 85 (19). doi:10.1029/2004EO190002
Gouretski, V. and K.P. Koltermann, 2007: How much is the ocean really warming? Geophysical Research Letters, 34, L01610. doi:10.1029/2006GL027834
Griffies, S.M., C. Boning, F.O. Bryan, E.P. Chassignet, R. Gerdes, H. Hasumi, A. Hirst, A.-M. Treguier, D. Webb, 2000: Developments in ocean climate modelling. Ocean Modelling, 2, pp. 123-192.
Griffies, S.M. and R.W. Hallberg, 2000: Biharmonic friction with a Smagorinsky viscosity for use in large-scale eddy-permitting ocean models. Monthly Weather Review, 128, pp. 2935–2946.
Griffies, S.M., 2009: Elements of MOM4p1: GFDL Ocean Group Tech. Rep. 6. NOAA/Geophysical Fluid Dynamics Laboratory, 444 pp.
Helm, K.P., N.L. Bindoff and J.A. Church, 2010: Changes in the global hydrological-cycle inferred from ocean salinity. Geophysical Research Letters, 37, L18701. doi:10.1029/2010GL044222
Hogg, A.M., M.P. Meredith, J.R. Blundell and C. Wilson, 2008: Eddy Heat Flux in the Southern Ocean: Response to Variable Wind Forcing. Journal of Climate, 21, pp. 608–620. doi:10.1175/2007JCLI1925.1
Page 22
Huang, R.X., W. Wang, L.L. Liu, 2006: Decadal variability of wind-energy input to the world ocean. Deep Sea Research II, 53, pp. 31-41.
Hunke, E.C. and Lipscomb, W.H., 2010: CICE: the Los Alamos Sea ice Model Documentation and Software 504 User’s Manual. LA-CC-06-012 Tech. Rep., 1–76.
Hundsdorfer, W. and R.A. Trompert, 1994: Method of lines and direct discretisation: a comparison for linear advection. Applied Numerical Mathematics, 13, pp. 469–490.
Ishii, M., A. Shouji, S. Sugimoto, and T. Matsumoto, 2005: Objective analyses of sea-surface temperature and marine meteorological variables for the 20th century using icoads and the Kobe collection. International Journal of Climatolology, 25, pp. 865–879.
Ishii, M. and M. Kimoto, 2009: Reevaluation of historical ocean heat content variations with time-varying XBT and MBT depth bias corrections. Journal of Oceanography, 65, pp. 287-299.
Josey, S. A., E. C. Kent, and P. K. Taylor, 1998: The Southampton Oceanography Centre (SOC) ocean–atmosphere heat, momentum, and freshwater flux atlas. Southampton Oceanography Centre Rep. 6, 30 pp.
Killworth, P. D., D. Stainforth, D. J. Webb, and S. M. Paterson, 1991: The development of a free-surface Bryan-Cox-Semtner ocean mode. Journal of Physical Oceanography, 21, pp. 1333–1348.
Kjellsson, J., P.R. Holland, G.J. Marshall, P. Mathiot, Y. Aksenov, A.C. Coward, S. Bacon, A.P. Megann and J. Ridley, 2015: Model sensitivity of the Weddell and Ross seas, Antarctica, to vertical mixing and freshwater forcing. Ocean Modelling, 94, pp. 141-152.
Page 23
Krueger, O., F. Schenk, F. Feser, and R. Weisse, 2013: Inconsistencies between long-term trends in storminess derived from the 20CR reanalysis and observations. Journal of Climate, 26, pp. 868– 874.
Kuhlbrodt, T. and J.M. Gregory, 2012: Ocean heat uptake and its consequences for the magnitude of sea level rise and climate change. Geophysical Research Letters, 39, L18608. doi:10.1029/2012GL052952
Lagerloef, G., R. Schmitt, J. Schanze, and H.-Y. Kao. 2010. The ocean and the global water cycle. Oceanography, 23(4), pp. 82–93. doi:10.5670/oceanog.2010.07
Lai, A.W., M. Herzog, H.-F. Graf., 2015: Two key parameters for the El Nino continuum: zonal wind anomalies and Western Pacific subsurface potential temperature. Climate Dynamics. doi:10.1007/s00382-015-2550-0
Large, W.G., J.C. McWilliams and S.C. Doney, 1994: Oceanic vertical mixing: A review and a model with a nonlocal boundary layer parameterization. Reviews of Geophysics, 32, pp. 363–403. doi:10.1029/94RG01872
Large W. and S. Yeager, 2004: Diurnal to decadal global forcing for ocean and sea ice models: the data sets and climatologies. Technical Report, Boulder: National Centre for Atmospheric Research, 105 pp.
Large, W.G. and S. Yeager, 2009: The global climatology of an interannually varying air-sea flux data set. Climate Dynamics, 33. doi:10.1007/s00382-008-0441-3
Lazier, J., R. Hendry, A. Clarke, I. Yashayaev, P. Rhines, 2002: Convection and restratification in the Labrador Sea, 1990-2000. Deep-Sea Research, 49, pp. 1819-1835.
Page 24
Levitus, S., J.I.Antonov, T.P. Boyer, C. Stephens, 2000: Warming of the world ocean. Sciences, 287, pp. 2225-2229.
Levitus, S., J.I. Antonov, and T.P. Boyer, 2005: Warming of the World Ocean, 1955-2003. Geophysical Research Letters, 32, L02604. doi:10.1029/2004GL021592
Levitus, S., J.I. Antonov, T.P. Boyer, O.K. Baranova, H.E. Garcia, R.A. Locarnini, A.V. Mishonov, J.R. Reagan, D. Seidov, E.S. Yarosh, and M.M. Zweng, 2012: World ocean heat content and thermosteric sea level change (0–2000 m), 1955–2010. Geophysical Research Letters, 39, L10603. doi:10.1029/2012GL051106
Marshall. J., K.C. Armour, J.R. Scott, Y. Kostov, U. Hausmann, D. Ferreira, T.G. Shepherd and C.M. Bitz, 2014: The ocean's role in polar climate change: asymmetric Arctic and Antarctic responses to greenhouse gas and ozone forcing. Philosophical Transactions of the Royal Society A, 372, 20130040. doi:10.1098/rsta.2013.0040
Marsland, S.J., and J.-O. Wolff, 2001: On the sensitivity of Southern Ocean sea ice to the surface freshwater flux. J. Geophys. Res. (Oceans), 106, pp. 2723-2741.
Meehl, G.A., J.M. Arblaster, J.T. Fasullo, A. Hu and K.E. Trenberth, 2011: Model-based evidence of deep-ocean heat uptake during surface-temperature hiatus periods. Nature Climate Change, 1, pp. 360–364. doi:10.1038/nclimate1229
Meredith, M.P., A. M. Hogg, 2006: Circumpolar response of Southern Ocean eddy activity to a change in the Southern Annular Mode. Geophysical Research Letters, 33, L16608. doi:10.1029/2006GL026499
Meredith, M.P., A.C.N. Garabato, A. M. Hogg and R. Farneti, 2012: Sensitivity of the Overturning Circulation in the Southern Ocean to Decadal Changes in Wind Forcing. Journal of Climate, 25, pp. 99-110.
Page 25
Morrison, A.K., England, M.H. and Hogg, A.M., 2015: Response of Southern Ocean Convection and Abyssal Overturning to Surface Buoyancy Perturbations. Journal of Climate, 28, pp. 4263-4278. doi:10.1175/JCLI-D-14-00110.1
Murray, R.J., 1996: Explicit generation of orthogonal grids for ocean models. Journal of Computational Physics, 126, pp. 251–273.
Myers, P.G., D. Deacu, 2004: Labrador Sea freshwater content in a model with a partial cell topographic representation. Ocean Modelling, 6, pp. 359-377.
Potter, R.A. and M.S. Lozier, 2004: On the warming and salinification of the Mediterranean outflow waters in the North Atlantic. Geophysical Research Letters, 31, L01202. doi:10.1029/2003GL018161
Purkey, S.G., G.C. Johnson, 2010: Warming of Global Abyssal and Deep Southern Ocean Waters between the 1990s and 2000s: Contributions to Global Heat and Sea Level Rise Budgets. Journal of Climate, 23, pp. 6336-6351.
Rayner, N. A., P. Brohan, D. E. Parker, C. K. Folland, J. J. Kennedy, M. Vanicek, T. J. Ansell, and S. F. B. Tett, 2006: Improved Analyses of Changes and Uncertainties in Sea Surface Temperature Measured In Situ since the Mid-Nineteenth Century: The HadSST2 Dataset. Journal of Climate, 19, pp. 446–469. doi:10.1175/JCLI3637.1
Redi, M.H., 1982: Oceanic isopycnal mixing by coordinate rotation. Journal of Physical Oceanography, 12, pp. 1154–1158.
Page 26
Schanze, J.J., R.W. Schmitt and L.L. Yu, 2010: The global oceanic freshwater cycle: A state-of-the-art quantification. Journal of Marine Research, 68, pp.569-595.
Schmitt, R.W., 2009: Salinity and the global water cycle. Oceanography, 21, pp. 12-19.
Schwarzkopf F.U. and C.W. Böning, 2011: Contribution of Pacific wind stress to multi-decadal variations in upper-ocean heat content and sea level in the tropical south Indian Ocean. Geophysical Research Letters, 38, L12602. doi:10.1029/2011GL047651
Seidel, D.J., Q. Fu, W.J. Randel and T.J. Reichler, 2008: Widening of the tropical belt in a changing climate. Nature Geoscience, 1, pp. 21-24. doi:10.1038/ngeo.2007.38
Simmons, H.L., S.R. Jayne, L.C.S. Laurent and A.J. Weaver, 2004: Tidally driven mixing in a numerical model of the ocean general circulation, Ocean Modelling, 6, pp. 245–263.
Skliris, N., R. Marsh, S.A. Josey, S.A. Good, C. Liu, R.P. Allan, 2014: Salinity changes in the World Ocean since 1950 in relation to changing surface freshwater fluxes. Climate Dynamics, 43 (3-4), pp. 709-736. doi:10.1007/s00382-014-2131-7
Sloyan, B.M., I.V. Kamenkovitch, 2007: Simulation of Subantarctic Mode and Antarctic Intermediate Waters in Climate Models. Journal of Climate, 20, pp. 5061-5080. doi:10.1175/JCLI4295.1
Smith, D.M. and J.M. Murphy, 2007: An objective ocean temperature and salinity analysis using
covariances from a global climate model. Journal of Geophysical Research, 112, C02022.
doi:10.1029/2005JC003172
Page 27
Stammer, D., 2008: Response of the global ocean to Greenland and Antarctic ice melting. Journal of Geophysical Research, 113, C06022. doi:10.1029/2006JC004079
Swart, N.C., J.C. Fyfe, 2012: Observed and simulated changes in the Southern Hemisphere surface westerly wind-stress. Geophysical Research Letters, 39, L16711. doi:10.1029/2012GL052810
Sweby, P., 1984: High-resolution schemes using flux limiters for hyperbolic conservation-laws. SIAM Journal of Numerical Analysis, 21, pp. 995–1011.
Taylor, K.E., R.J. Stouffer and G.A. Meehl, 2012: An Overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, 93, pp. 485-498, doi:10.1175/BAMS-D-11-00094.1
Trenberth, K., L. Smith, T. Qian, A. Dai, and J. Fasullo, 2007: Estimates of the global water budget and its annual cycle using observational and model data. Journal of Hydrometeorology, 8, pp. 758–769.
Uppala, S.M., P.W. Kållberg, A.J. Simmons, U. Andrae, V. Da Costa Bechtold, M. Fiorino, J.K. Gibson, J. Haseler, A. Hernandez, G.A. Kelly, X. Li, K. Onogi, S. Saarinen, N. Sokka, R.P. Allan, E. Andersson, K. Arpe, M.A. Balmaseda, A.C.M. Beljaars, L. Van De Berg, J. Bidlot, N. Bormann, S. Caires, F. Chevallier, A. Dethof, M. Dragosavac, M. Fisher, M. Fuentes, S. Hagemann, E. Hólm, B.J. Hoskins, L. Isaksen, P.A.E.M. Janssen, R. Jenne, A.P. Mcnally, J.-F. Mahfouf, J.-J. Morcrette, N.A. Rayner, R.W. Saunders, P. Simon, A. Sterl, K.E. Trenberth, A. Untch, D. Vasiljevic, P. Viterbo and J. Woollen, 2005: The ERA-40 re-analysis. Quarterly Journal of the Royal Meteorological Society, 131(612), pp. 2961-3012.
Valcke, S. 2006: OASIS3 User Guide (prism 2-5). PRISM Support Initiative, Report No. 3, CERFACS, Toulouse, France, 68 pp.
